I’ve been experimenting with AI coding tools a lot recently.

They’re great for getting something working fast.

But I’ve noticed a pattern:

Things look clean.
They run fine.

But I don’t always fully understand everything that’s happening anymore.

Especially when it starts touching:

• APIs

• data

• permissions

• or multiple layers of the system

For MVPs, that’s fine.

But for production, it feels different.

Some people here mentioned they:

• only use AI for small scoped tasks

• review everything line by line

• or spend more time in planning before generating anything

That feels like the right direction.

Because the issue doesn’t seem to be “AI writes bad code.”

It’s more:
→ how easily we start trusting code once it works
→ and how that affects review depth

I’m curious how others are handling this.

Do you:

• treat AI as a helper you fully control

• or let it generate larger parts of the system

And more importantly:

Do you trust AI-generated code enough to push it to production?